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Volumn 11, Issue 2, 2002, Pages 289-305

A computational approach for full nonparametric Bayesian inference under Dirichlet process mixture models

Author keywords

Dirichlet process mixing; Extreme value distributions; Functionals; Markov chain Monte Carlo; Survival data distributions

Indexed keywords


EID: 0036017464     PISSN: 10618600     EISSN: None     Source Type: Journal    
DOI: 10.1198/106186002760180518     Document Type: Article
Times cited : (100)

References (42)
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  • 15
    • 0001787029 scopus 로고
    • Bayesian density estimation by mixtures of normal distributions
    • eds. M. H. Rizvi, J. S. Rustagi, and D. Siegmund, New York: Academic Press
    • (1983) Recent Advances in Statistics , pp. 287-302
  • 21
    • 0001677650 scopus 로고    scopus 로고
    • Markov chain monte carlo in approximate dirichlet and beta two-parameter process hierarchical models
    • (2000) Biometrika , vol.87 , pp. 371-390
    • Ishwaran, H.1    Zarepour, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.